• ISSN: 2010-3646
    • Abbreviated Title: Int. J. Social. Scienc. Humanit.
    • Frequency: Bimonthly (2011-2014); Monthly (2015-2018); Quarterly (Since 2019)
    • DOI: 10.18178/IJSSH
    • Editor-in-Chief: Prof. Aurica Briscaru
    • Executive Editor: Mr. Ron C. Wu
    • Abstracting/ Indexing: Google Scholar, Index Copernicus, Crossref, Electronic Journals Library
    • E-mail: ijssh@ejournal.net
IJSSH 2015 Vol.5(11): 937-943 ISSN: 2010-3646
DOI: 10.7763/IJSSH.2015.V5.583

The Development of Algo-Heuristic Model: To Improve Student Learning Acquisition in Statistics at Elementary School Teacher Education

Abstract—The purpose of this study is to test the effectiveness of algo-heuristic models in improving the students’ academic achievement of elementary school teacher education. This study consists of: (1) the first phase of testing (small group) carried out by instructional design and expert statistical learning, (2) the second phase of testing (large group) conducted by the course lecturer, and (3) the effectiveness of testing conducted on students. Procedures focus on the development of an evaluation of algo-heuristic theory. Evaluation consists of three stages. Stage 1, to test the theoretical product quality Expert test, subjects (instructional design and quality) are asked to rate the acceptability of algo-heuristics as to usefulness, feasibility and accuracy before being tested on students. Stage 2, test to a small group of Elementary School Teacher Education’s lecturers. This means that before the students are presented with algo-heuristics the lecturers are first equipped with an algo-heuristic guide. The goal is for teachers to understand the concept. Stage 3, large group testing to determine the effectiveness of the implementation of the algo-heuristic model to improve the learning of statistics students using pre-experimental research. The pre-test mean score is 61.43. The post-test mean score is 69.48. There is a difference between the scores of 8.05. This shows a relative increase of 13.1%. T-test analysis results give a score of -5.111 with a probability of 0.000. Score statistics show a significant increase and the performance statistics indicate a rising trend. This indicates an adequate statistical basis for algo-heuristic learning to be implemented.

Index Terms—Academic achievement, acquisition of statistical learning, algo-heuristic, student’s evaluation.

Rufi’i is with the Postgraduate program, Instructional Technology Study Program, University PGRI Adi Buana Surabaya, Indonesia (e-mail: rufii.unipa2013@gmail.com).


Cite: Rufi’i, " The Development of Algo-Heuristic Model: To Improve Student Learning Acquisition in Statistics at Elementary School Teacher Education," International Journal of Social Science and Humanity vol. 5, no. 11, pp. 937-943, 2015.

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